Throughout a doctor-patient encounter a physician generally must keep precise records corresponding to the patient. These patient records include information relating to patient history, current problems, diagnoses for a particular visit, courses of treatment and medical reports. These records serve many functions relating to the actual treatment of the patient in order to safeguard proper care. More recently, proper records and documentation are also required for physicians to create proper billing statements so they can receive payments from a patient's insurance provider for services rendered.
One important aspect that must be provided for in a claims submission to a payment provider is a diagnosis relating to the patient which justifies actions taken by a physician. Without a diagnosis in a claim submission, many actions taken by a physician will not be deemed to be necessary by a payment provider and therefore will not be covered for payment. A diagnosis is usually provided on a claim submission in the form of a code. Currently, codes which are standardized under the International Classification of Diseases 9 standard (ICD-9) are widely utilized. There are approximately 13,000 codes in the ICD-9 standard which cover a broad spectrum of medicine. For billing purposes, a physician will generally employ a biller/coder that takes a physician's written diagnosis and matches it to a specific ICD-9 code and enters it onto a claim form for submission. This system generally works as the codes are sufficiently broad enough that a coder can look up the proper code. Additionally, because a physician may work in specific areas of medicine, a coder can become familiar with common codes.
Beginning on Oct. 1, 2014, many in the medical field will be required to utilize codes in the ICD-10 for billing purposes. ICD-10 utilizes over 68,000 codes and can be very specific (e.g. identifies right versus left side, code allows for description of comorbidities, manifestations, etiology/causation, complications, detailed anatomic location, sequelae, degree of impairment, biologic and chemical agents, phase/stage, lymph node involvement, age related, procedure or implant related, etc.). This raises many issues in the overall practice of medicine both on the billing side and during an actual patient encounter due to the fact that more/different details may be required to determine a proper diagnosis code.
For example, currently if a patient sees a physician because of a broken arm, a physician may note that the patient has a “closed radius shaft fracture” under ICD-9 (which corresponds to code 813.21). However, if the same terminology was utilized under ICD-10, the description would be a “closed unspecified fracture of the shaft of an unspecified radius.” Because multiple portions needed to generate a code would remain unspecified, payment to a physician could be delayed or even rejected. Further, it is notable that for the example of a fractured radius there are 27 possible ICD-9 codes whereas there are 2,960 possible ICD-10 codes. Because of this, not only has the billing process been altered by requiring coders to manage more detailed possibilities for diagnoses and procedures, additional data may need to be obtained/documented by a physician during a patient encounter beyond what a physician is accustomed to obtaining during the normal course of practicing medicine.
One current solution to this problem that has been implemented utilizes a natural language processing engine to locate and determine an appropriate code. In this solution, a computing device receives a typed or dictated natural language input and automatically searches the ICD-10 code database for proper diagnosis codes. This solution raises multiple issues. First, the technology underlying the natural language searches is still unreliable and inaccurate. Further, because a physician does not necessarily know what new information is needed, the proper terminology to plug into the natural language algorithm may not be present.
Another approach entails simply conducting a key word search whereupon a physician or billing/coding professional enters a diagnosis and/or other key terms. However, in many cases depending on the type of problems exhibited by a patient, a key word search may yield 500 or more results. These results would then need to be reviewed and a code would be selected. This approach is not always feasible and/or conducive to finding a proper code in an efficient manner. Further, as with the natural language solution, because the physician may not necessarily know what new information is needed, the proper terminology to plug into the search engine may not be present in the patient documentation.